Accumulating and uncovering reliable knowledge over the Internet can be a challenge. Currently, many algorithms for returning search results via common search engines include paid advertisements. Popular content across a broad spectrum of intents, including commercial ones, tends to be pushed up in positions by a ranker of the search engine, which causes results served up by the search engines to reflect the behavior of their users. Therefore, the bias of users can be reflected directly in the results. In addition, the click stream can cause popular articles to become even more popular, establishing and reinforcing a consensus about what is and is not important. Ranking of results may be based on the number of “clicks” a link may get over time, which can result in “clickbait” attempts to increase visibility, or may be based on keyword tags, which can also be subject to manipulation.
Furthermore, misinformation or disinformation on the web can lead to serious errors. For example, in search boxes providing mined answers, researching on the web can include wrong and partially wrong or outdated results. Mined answers present what looks like authoritative facts. Superficial research can lead to students picking up wrong or conflated information, particularly when the results are scrapes (e.g., via bots across the web) combining different sources, which can also suffer the same problems as mentioned above.